Robotics & Automation 2019

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R A C O N T E U R . N E T 13 The industrial adoption of robotic process automation promises improved efficiency, but silly slip ups mean businesses miss out Learning from the first wave of automation he robot is no stranger to heavy industry, but its vir- tual co-worker, robotic pro- cess automation (RPA), is only just beginning to find a place within the industrial sector. The tech- nology's clever software robots can fulfil repetitive and time-con- suming tasks, and offer a multitude of benefits from improved accuracy to cost-savings. However, with RPA failures a com- mon occurrence in its early adop- tion, it's clear that initial imple- mentation of the technology has not proved to be smooth sailing for many businesses. For multinational consultancy EY, RPA failures are all too familiar, having witnessed 30 to 50 per cent of initial projects fail. Companies developing the technology claim it can transform operations, but if it's as favourable as they say, why are there so many RPA failures? In actual fact, the tendency for RPA to fail is not down to the tech - nology itself. This instead repre- sents a misuse and misunderstand- ing of the technology. "A fundamental mistake which is commonly made is that process automation is seen as a pure tech- nology implementation delivered by IT," says Neil MacLean, partner at EY UK and Ireland. Other common errors that have led to RPA failures include mis- judging what happens after adopt- ing automation, thinking robots are the whole solution, directing RPA technology at the wrong processes and assuming the skills necessary for a pilot are up to scratch for real operations. The good news is that because most RPA failures are the result of human error, rather than the tech- nology itself, businesses can learn from their past mistakes and simply take a different approach. Aaron Bultman, director of prod- uct at Nintex, which has its own RPA platform, says to avoid making the same mistake twice, a business must map the entire process of adoption to ensure it has a full understanding. The company should involve subject matter experts throughout, so incor- rect assumptions aren't applied, and remember that just because one process is not a good fit for RPA, it doesn't mean the business should stop using the technology. RPA projects that succeed teach us the same lessons as those which fail. And there's a lot to learn from busi- nesses that are thriving as a result of implementing the technology. "While there are many use-cases of RPA in the office environment, where it really comes into its own is in heavy industries such as ship- ping, manufacturing and mining," says Johan Carstens, chief technol- ogy officer of manufacturing and automotive at Fujitsu. "The biggest priority in these industries is worker safety and RPA is being used to reduce the dependency on humans in high-risk tasks." EY is working with a mining com- pany to develop a model that helps its metallurgical team increase ore recovery. The model is based on mathematical pattern recognition techniques, or machine-learning, and uses data automations to make recommendations. Nasa uses Eggplant's RPA plat - form to automate various processes in its Orion space vehicle, which is being prepared for a mission to Mars. "Equipped with three main displays to monitor and control the spacecraft, to ensure the software behind the glass displays operates without faults, rigorous automated testing is needed," says Dr John Bates, chief executive of Eggplant. "RPA is supporting Nasa's mission to take humans deeper into space." The cement manufacturing indus - try uses machines to process a vari- ety of block products and the con- crete mix used to generate these blocks must be highly controlled. In the past, this process was completed manually, but nowadays RPA is used to open and close gates, measure moisture levels, and reduce human interaction to eliminate error. There are also examples of RPA being successfully implemented by companies in the automotive industry, such as Renault, as well as in the production of radiation oncology systems, by companies including Accuray, and within supply chain businesses. By saving money, reducing human error and minimising repetitive tasks to free up time for employees, RPA has the capacity to transform heavy industry. But businesses must apply the right methods of adop- tion to ensure they make the most out of the software and do not leave stakeholders wondering why they invested in the technology in the first place. Paul Hennessy/NurPhoto via Getty Images Siemens, Europe's largest manufacturer, has adopted robotic process automation (RPA) as part of the company's digital transformation. When first introducing RPA into the business, a big challenge for Siemens was addressing automating an entire business processes chain. The company realised its RPA platform needed development. In turn, the company created an open ecosystem to enable intelligent automation technologies to be augmented by its digital workforce. This tech ecosystem includes IBM Watson for natural language understanding, Google Cloud for natural language translation, Microsoft for chatbot framework and orchestration, Blue Prism's connected RPA platform, and a secure connection to Siemens' workflows, data lake and other applications "To ensure that we experience rapid results in the implementation of RPA projects and business successes, the development of in-house RPA expertise and close co-operation between IT teams and business leaders is critical," says Nikolas Barth, head of innovation and digitalisation at Siemens. Originally the company had 50 processes and 80,000 working hours automated; after implementing the technology, and in less than a year, there were 170 additional processes and more than 280,000 extra hours automated. Europe's biggest manufacturer implements RPA Alexandra Leonards T I N D U S T R I A L A D O P T I O N 30-50% EY 2017 of initial robotic process automation projects fail A robot in operation during the first public tour of the newest Amazon Robotics fulfillment center in Orlando in April

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